CAJ | 학술논문

基于稀疏表示的超分辨率重构算法效果依赖于样本图像信息，难以保证重构质量；基于图像结构自相似的算法利用了图像自身的附加信息，但是这些信息不足以获得很好的重构效果。本文综合利用样本图像信息和待处理低分辨率图像自身信息，提出了一种新的方法。在基于稀疏表示的框架下把与待重建图像相似的高分辨率样本图像信息提取出来用于重构，利用低分辨率图像自身的附加信息对上一步的重构图像进行修复，进一步提高重构质量。数值实验结果表明，本算法对图像的细节部分具有更好的重构效果。
기우희소표시적초분변솔중구산법효과의뢰우양본도상신식，난이보증중구질량；기우도상결구자상사적산법이용료도상자신적부가신식，단시저사신식불족이획득흔호적중구효과。본문종합이용양본도상신식화대처리저분변솔도상자신신식，제출료일충신적방법。재기우희소표시적광가하파여대중건도상상사적고분변솔양본도상신식제취출래용우중구，이용저분변솔도상자신적부가신식대상일보적중구도상진행수복，진일보제고중구질량。수치실험결과표명，본산법대도상적세절부분구유경호적중구효과。
T he reconstructed image quality of super-resolution based on sparse representation depends on the information of high-resolution image database ,the result can not be guaranteed .Super-resolution based on image structural similarity only uses the additional information contained in the given low-reso-lution image itself ,but the information is not enough to get an ideal reconstructed image .In order to use both training database and the given low-resolution image ,a new method is put forward in this paper . First ,use the sparse representation based algorithm to reconstruct the image ;and then ,use the addition-al information contained in the low resolution image to repair the achieved image in the first step ,en-hance the quality in advance .The simulation result indicates that the method perform better than the two algorithm mentioned above .